CN103870552A - Scrambling and recovery method for GIS (Geographic Information System) vector data line and plane graphic layer - Google Patents

Abstract

The invention discloses a scrambling and recovery method for a GIS (Geographic Information System) vector data line and plane graphic layer and belongs to the field of geographic information security. The method is based on quasi-affine transformation in a finite integer field and mainly comprises the following processes: 1) a scrambling process, which comprises the steps of constructing a vector data finite field scrambling transformation space, determining transformation rules, generating transformation parameters, performing global scrambling, removing virtual points, forming scrambled vector data and the like; 2) a recovery process, which comprises the steps of generating inverse transformation parameters, performing global anti-scrambling, forming and displaying recovered vector data and the like. The method disclosed by the invention has the characteristics of randomness, reversibility and the like, the recovery transformation has a simple analytical expression, recovery can be realized without performing periodic iteration and effectively technical means are provided for safe transmission, packaging and storage of geographic spatial data.

Description

A kind of scramble and method of reducing of GIS vector data line face figure layer

Technical field

The invention belongs to geography information security fields, be specifically related to a kind ofly carry out the scramble of GIS vector data line face figure layer and the method for reduction based on intending affined transformation on limited integer field, can realize safe transmission and the access of Geographic Information System field vector data.

Background technology

GIS vector data has advantages of high precision, magnanimity, easily storage, robotization processing and can't harm the traditionally on paper maps such as convergent-divergent incomparable, range of application is extremely extensive, but in the network storage and transmitting procedure, GIS vector data is easy to illegally be intercepted and distort, therefore, most important for the research of GIS vector data safety.Current existing encryption method is mainly to realize encryption for the change of coordinate precision, and it is thicker mostly to encrypt granularity level, do not consider the topological relation between key element, therefore set about from the angle of preferential destruction spatial relationship, the GIS vector data disorder method of upsetting based on an order is a kind of important information encryption and effective safe enhancements, significant for the security that improves network information transfer.

The principle of GIS vector data scramble is sequence number (x, a y) scramble to be transformed to a sequence number (x ', y ') locate, and gives me a little by former the some key element that property value assignment that (x, y) locate is located to (x ', y ').Daubechies, I. (1996) has set forth the reversible transformation thought by integer-to-integer, and Zhu Guibin (2003) etc. has provided the Image Scrambling Algorithm based on intending affined transformation.

Integer lifting conversion can realize the reversible transformation of integer-to-integer:

Affined transformation for following special shape:

$\left(\begin{array}{c}{x}^{\′}\\ y^{\′}\end{array}\right)=\left(\begin{array}{cc}1& \mathrm{\α}\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)---\left(1\right)$

Can construct his corresponding integer transform is

Wherein

represent the integral part (symbol of x

represent rounding operation), add 0.5 to round off to realize.Can find out from formula (2), if input x, y is integer, the x ' arriving through calculating so, and y ' must be also integer, it is inversely transformed into:

Formula (2) is the integer lifting conversion of formula (1), and formula (3) is the contrary integer lifting conversion of formula (1).In addition, the cascade of integer lifting conversion also can realize the reversible transformation of integer-to-integer.

Lifting Transform on limited integer field also can be realized the reversible transformation of limited integer field to limited integer field:

Definition conversion is that { (x, y): 0≤x<M, 0≤y<N} is to himself single mapping and full mapping for disperse drop field.For formula (1), when limiting 0≤x<M, when 0≤y<N, can construct Lifting Transform on corresponding limited integer field as follows:

Corresponding is inversely transformed into:

Equally, the cascade of the Lifting Transform on limited integer field also can realize the reversible transformation to limited integer field on limited integer field.

And the feature of integer lifting conversion is basically identical in the requirement of the integer transform of the limited space of GIS vector data and dotted line sequence number and Galois field, therefore this transform method can be applied to vector data scramble well.But the line feature that GIS vector data line face figure layer is not waited by a key element number forms, and belongs to unsaturated matrix, not in full conformity with the requirement of Galois field.Therefore, in order to facilitate Organization of Data conversion, improve data-handling efficiency, vector data " can be supplemented " to one-tenth " square formation " form, be built with confinement scramble transformation space, and then realize the overall scramble between GIS vector data factor kind and key element.

Summary of the invention

The object of the invention is to: the plan affine transformation method on principle, limited integer field based on topological relation between preferential destruction key element and GIS vector data feature, propose a kind of scramble and method of reducing for line Noodles type GIS vector data, thereby provide technical support for safe transmission, the sealed storage etc. of GIS vector data.

To achieve these goals, the technical scheme that the present invention takes is:

Scramble and the method for reducing of GIS vector data line face figure layer, comprise the steps:

(1) scramble process

Step 11: structure vector data Galois field scramble transformation space

A) open a line Noodles type GIS vector data file, read successively the spatial data of each key element, and total number I of line face key element and the some key element number J that contains the line face of counting at most;

B) structure vector data Galois field space, determines that { wherein x is the sequence number of vector data line face key element for (x, y): 0≤x<I, 0≤y<J}, and y is the sequence number of a key element for the disperse drop field of scramble conversion;

Step 12: determine scramble transformation rule

The general type of affined transformation is

$\left\{\begin{array}{c}{x}^{\&prime;}=\mathrm{ax}+\mathrm{by}+e\\ y^{\&prime;}=\mathrm{cx}+\mathrm{dy}+f\end{array}---\left(1\right)\right.$

When coefficient meets $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|=1,$ C ≠ 0 o'clock, formula (1) can be simplified and is designated as:

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)---\left(2\right)$

This conversion is to be limited to disperse drop field { (x, y): 0≤x<I, on 0≤y<J}, by translation parameters e, f incorporates in last integer lifting conversion and simply rounds off and round, other parts realize with integer lifting conversion, can realize the plan affined transformation of formula (1) on limited integer field, and last integer lifting conversion is as follows:

It is inversely transformed into accordingly:

Wherein,

represent round computing, mod represents complementation, in integer lifting conversion at different levels, introduce the nonlinear computing of rounding off, making last result is no longer traditional affined transformation, the inverse transformation that this integer is intended affined transformation necessarily exists, and is the one-to-one transformation on limited integer field;

Step 13: transformation parameter generates

According to formula (2), need to generate the parameter a of integer lifting conversion ₁, a ₂, a ₃, and translation parameters e, f; Utilize chaos system

, input key file grey iterative generation x _n; To x _ncarry out interval fetch bit, obtain the iterations n of Logistic chaos system ₁, n ₂, n ₃, n _e, n _f; Logistic chaos system is distinguished to iteration n again ₁, n ₂, n ₃, n _e, n _finferior, can obtain the parameter a that integer lifting converts ₁, a ₂, a ₃and translation parameters e, f;

Step 14: overall scramble

A) according to the scramble transformation rule in transformation parameter, step 12 in step 13 and formula (5), the plan affined transformation of a key element sequence number is carried out in pointwise;

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)\left(\mathrm{mod}\begin{array}{c}I\\ J\end{array}\right)---\left(5\right)$

B) the some key element that (x, y) located in pointwise moves to and intends after affined transformation (x ', y ') and locates, and the some essential factors space data that original (x, y) located are all assigned to the some key element that (x ', y ') locates;

Step 15: remove imaginary point and form the vector data RE after scramble

After a key element sequence number scramble conversion, carry out interlacing point key element by the sequence number of line face key element, line face key element corresponding to real point add one by one to; If run into imaginary point, the real point after it is put to sequence number really and charge to attribute z, constant to ensure the vector data points key element number after scramble, thus form the line face figure layer data R after scramble ^e;

Step 16: by the data after pointwise scramble, write vector data R ^e, form the data file after scramble;

(2) reduction process

Step 21: restoring transformation parameter generates

According to the method for the step 13 in said process (), input key file, generates the parameter a1 that becomes restoring transformation, a2, a3 and translation parameters e, f;

Step 22: the overall situation unrest that is inverted

A) according to going back raw parameter and inverse transformation rule, the inverse transformation of affined transformation is intended in pointwise; Meanwhile, need whether first judging point key element attribute z value be 0 when reduction; If 0, put key element sequence number y ' participation inverse operation; Otherwise z value replaces y ' participation inverse operation;

B) spatial data of will (x ', y ') locating a key element is all assigned to the some key element that (x, y) locates;

Step 23: after inverse transformation, carry out interlacing point key element by the sequence number of line face key element, a key element is added in corresponding line face key element one by one, form the line face figure layer data R after scramble ^dand show.

The present invention is based on plan affine transformation method on principle, the limited integer field of topological relation between preferential destruction key element and the feature of GIS vector data, for line Noodles type GIS vector data, carry out scramble and the reduction of line face key element, the method has the feature such as randomness, reversibility, can provide effective technological means for the safe transmission of geographical spatial data, sealed storage.

Brief description of the drawings

Fig. 1 is data disorder process flow diagram in the inventive method;

Fig. 2 is data reduction process flow diagram in the inventive method;

Fig. 3 is the schematic diagram of processing imaginary point in the inventive method under Galois field;

Fig. 4 is the experimental data that the embodiment of the present invention adopts;

Fig. 5 is the scramble design sketch of vector data in the embodiment of the present invention;

Fig. 6 is the reduction effect figure of scramble vector data in the embodiment of the present invention.

Embodiment

Below in conjunction with drawings and Examples, be described in further details.

The present embodiment is selected a typical shp line chart layer data R, for the generation of transformation parameter, and the whole process (face figure layer data can be taked same method) of the scramble of vector data and reduction, further description the present invention.The present embodiment selects shp form vector data China 1:400 ten thousand provincial boundaries line chart layer (as Fig. 4) as experimental data.

(1) for the scramble process of line chart layer data

Step 11: be configured with confinement scramble transformation space

A) open shp line chart layer data, read successively the information of contained some key element of each line feature in line chart layer data, in the present embodiment, total number I of line feature is 1785, and the some key element number J that contains the line of counting is at most 500;

B) structure vector data Galois field space, determines that { wherein x is the sequence number of vector data line feature for (x, y): 0≤x<1785,0≤y<500}, and y is the sequence number of a key element for the disperse drop field of scramble conversion.

Step 12: determine scramble transformation rule

The general type of affined transformation is

$\left\{\begin{array}{c}{x}^{\&prime;}=\mathrm{ax}+\mathrm{by}+e\\ y^{\&prime;}=\mathrm{cx}+\mathrm{dy}+f\end{array}---\left(1\right)\right.$

Wherein $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|\&NotEqual;0,$ Write it the form of matrix as:

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}a& b\\ c& d\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)---\left(2\right)$

For the general affine transformation of formula (1) definition, when coefficient meets $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|=1,$ C ≠ 0 o'clock, can formula (1) be decomposed as follows:

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}a& b\\ c& d\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)=\left(\begin{array}{cc}1& \frac{a-1}{\mathrm{<figure-callout\; id="0"\; label="c"\; filenames="HDA0000472093900000012.png"\; state="\{\{state\}\}">c</figure-callout>}}\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ c& 1\end{array}\right)\left(\begin{array}{cc}1& b+\frac{1-a}{\mathrm{<figure-callout\; id="0"\; label="c\; d"\; filenames="HDA0000472093900000012.png"\; state="\{\{state\}\}">c</figure-callout>}}d\\ 0& \mathrm{ad}-\mathrm{bc}\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)---\left(3\right)$

Can simplify and be designated as:

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)---\left(4\right)$

This conversion is to be limited to disperse drop field { (x, y): 0≤x<I, on 0≤y<J}, by translation parameters e, f incorporates in last integer lifting conversion and simply rounds off and round, other parts realize with integer lifting conversion, can realize the plan affined transformation of formula (1) on limited integer field.Last integer lifting conversion is as follows:

It is inversely transformed into accordingly:

Wherein,

represent round computing, mod represents complementation, in integer lifting conversion at different levels, has introduced the nonlinear computing of rounding off, and making last result is no longer traditional affined transformation.The inverse transformation that this integer is intended affined transformation necessarily exists, and is the one-to-one transformation on limited integer field.

Step 13: generate transformation parameter

Input key file, utilizes chaos system grey iterative generation x _n; To x _ncarry out interval fetch bit, obtain the iterations n of Logistic chaos system ₁, n ₂, n ₃, n _e, n _f; Logistic chaos system is distinguished to iteration n again ₁, n ₂, n ₃, n _e, n _finferior, the parameter a that obtains integer lifting conversion is processed in location value expansion ₁=0.13, a ₂=0.47, a ₃=0.88, and translation parameters e=10.26, f=5.65.

The randomness of these 5 transformation parameters, greatly facilitates the selection of key, has increased the security of system, and the selection of parameter has determined the size of data disorder degree to a certain extent.

Step 14: overall scramble

A) this conversion is to be limited to disperse drop field { (x, y): 0≤x<1785, on 0≤y<500}, by translation parameters e, f incorporates in last integer lifting conversion and simply rounds off and round, other parts realize with integer lifting conversion, and concrete conversion process is as follows:

So transformation for mula is as follows:

B) substitution transformation parameter, the plan affined transformation of a key element sequence number is carried out in pointwise, and the spatial data that original (x, y) locates a key element is all assigned to the some key element that (x ', y ') locates.

As first key element of Article 1 line, the some key element that (0,0) is located, intend affined transformation through above-mentioned transformation for mula and locate to (11,6), be i.e. the 7th of the 12nd bar of line the point, all spatial informations of the some key element of namely (0,0) being located are all assigned to the some key element of (11,6) locating.

Step 15: remove imaginary point and form the vector data R after scramble ^e

After the conversion of said method scramble, carry out interlacing point key element by line feature sequence number, real point is added in corresponding line feature one by one.Because contained some key element number of each line feature is inconsistent, belong to unsaturated matrix, the some key element number of the place line feature after conversion is uncertain, can before real point, there is imaginary point, as shown in Figure 3, if the real point that (0,4) is located transforms to (4,7) real point of locating, but (4,4) (4,5) (4,6) locate not have point, be imaginary point.Constant in order to ensure the vector data points key element number after scramble, need to remove imaginary point, and the real point after imaginary point is put to sequence number really and charge to attribute z.After scramble conversion, front 69 some key elements of Article 1 line feature are all imaginary point, need to remove imaginary point and the real point after imaginary point are put to sequence number really and charge to attribute z, and now the sequence number of first real point is (0,0), and its z value is 69.According to the method, real point is read in to corresponding line feature one by one, form the vector data R after scramble ^e.The point key element that in figure, (0,4) is located is located to sequence number (4,3) after scramble conversion, and its attribute z value is 7.

Step 16: after pointwise is disposed, form the vector data R after scramble ^e.

(2) for the reduction process of line chart layer data

Step 21: restoring transformation parameter generates

According to the method for the step 13 in said process (), input key file, generates the parameter a that becomes restoring transformation ₁, a ₂, a ₃and translation parameters e, f.

Step 22: the overall situation unrest that is inverted

A) cascade of the Lifting Transform on limited integer field can realize the reversible transformation to limited integer field on limited integer field, and concrete inverse transformation process is as follows:

Order $\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)\left(\mathrm{mod}\begin{array}{c}I\\ J\end{array}\right)=\left(\begin{array}{c}p\\ q\end{array}\right)\left(\begin{array}{c}e\\ f\end{array}\right)\left({\mathrm{mod}}_J^I\right)(p\&GreaterEqual;0,q\&GreaterEqual;0)$

?

So,

B) also raw parameter of substitution, an inverse transformation for key element sequence number is carried out in pointwise.Whether meanwhile, need first judging point key element attribute z value when inverse transformation is 0.If 0, y ' participation inverse operation; Otherwise z value replaces y ' participation inverse operation.Spatial information and the property value of will (x ', y ') after inverse transformation locating a key element are assigned to the some key element that (x, y) locates.

Step 23: after inverse transformation, carry out interlacing point key element by line feature sequence number, a key element is added in corresponding line feature one by one, form the shp line face figure layer data R after scramble ^d.

(3) experimental analysis

From above-described embodiment (Fig. 4,5,6): the present invention is based on the feature of intending affine transformation method and GIS vector data on the principle of topological relation between preferential destruction key element, limited integer field, for shp line chart layer data, carry out scramble and the reduction of line feature.In the present invention, its restoring transformation has succinct analytical expression, can recover without the iteration of carrying out cycle times, and scramble data after treatment have identical or close institutional framework and data layout with raw data, thereby there is higher treatment effeciency, security preferably, can the security of effective guarantee geographical spatial data in data transmission, sealed storage.

The embodiment of the present invention is only carried out scramble and reduction processing with the line chart layer data of shp form, and face key element can be regarded the line of sealing as, and the method is also applicable to face figure layer data; Also the scramble that is applicable to the extended formatting GIS vector datas such as GML, E00, MIF is processed with reduction simultaneously.

Claims (1)

1. scramble and the method for reducing of GIS vector data line face figure layer, is characterized in that, comprises the steps:

(1) scramble process

Step 11: structure vector data Galois field scramble transformation space

A) open a line Noodles type GIS vector data file, read successively the spatial data of each key element, and total number I of line face key element and the some key element number J that contains the line face of counting at most;

B) structure vector data Galois field space, determines that { wherein x is the sequence number of vector data line face key element for (x, y): 0≤x<I, 0≤y<J}, and y is the sequence number of a key element for the disperse drop field of scramble conversion;

Step 12: determine scramble transformation rule

The general type of affined transformation is

$\left\{\begin{array}{c}{x}^{\&prime;}=\mathrm{ax}+\mathrm{by}+e\\ y^{\&prime;}=\mathrm{cx}+\mathrm{dy}+f\end{array}---\left(1\right)\right.$

When coefficient meets $\left|\begin{array}{cc}a& b\\ c& d\end{array}\right|=1,$ C ≠ 0 o'clock, formula (1) can be simplified and is designated as:

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)---\left(2\right)$

This conversion is to be limited to disperse drop field { (x, y): 0≤x<I, on 0≤y<J}, by translation parameters e, f incorporates in last integer lifting conversion and simply rounds off and round, other parts realize with integer lifting conversion, can realize the plan affined transformation of formula (1) on limited integer field, and last integer lifting conversion is as follows:

It is inversely transformed into accordingly:

Wherein,

represent round computing, mod represents complementation, in integer lifting conversion at different levels, introduce the nonlinear computing of rounding off, making last result is no longer traditional affined transformation, the inverse transformation that this integer is intended affined transformation necessarily exists, and is the one-to-one transformation on limited integer field;

Step 13: transformation parameter generates

According to formula (2), need to generate the parameter a of integer lifting conversion ₁, a ₂, a ₃, and translation parameters e, f; Utilize chaos system input key file grey iterative generation x _n; To x _ncarry out interval fetch bit, obtain the iterations n of Logistic chaos system ₁, n ₂, n ₃, n _e, n _f; Logistic chaos system is distinguished to iteration n again ₁, n ₂, n ₃, n _e, n _finferior, can obtain the parameter a that integer lifting converts ₁, a ₂, a ₃and translation parameters e, f;

Step 14: overall scramble

A) according to the scramble transformation rule in transformation parameter, step 12 in step 13 and formula (5), the plan affined transformation of a key element sequence number is carried out in pointwise;

$\left(\begin{array}{c}{x}^{\&prime;}\\ y^{\&prime;}\end{array}\right)=\left(\begin{array}{cc}1& a_1\\ 0& 1\end{array}\right)\left(\begin{array}{cc}1& 0\\ a_2& 1\end{array}\right)\left(\begin{array}{cc}1& a_3\\ 0& 1\end{array}\right)\left(\begin{array}{c}x\\ y\end{array}\right)+\left(\begin{array}{c}e\\ f\end{array}\right)\left(\mathrm{mod}\begin{array}{c}I\\ J\end{array}\right)---\left(5\right)$

B) the some key element that (x, y) located in pointwise moves to and intends after affined transformation (x ', y ') and locates, and the some essential factors space data that original (x, y) located are all assigned to the some key element that (x ', y ') locates;

Step 15: remove imaginary point and form the vector data R after scramble ^e

After a key element sequence number scramble conversion, carry out interlacing point key element by the sequence number of line face key element, line face key element corresponding to real point add one by one to; If run into imaginary point, the real point after it is put to sequence number really and charge to attribute z, constant to ensure the vector data points key element number after scramble, thus form the line face figure layer data R after scramble ^e;

Step 16: by the data after pointwise scramble, write vector data R ^e, form the data file after scramble;

(2) reduction process

Step 21: restoring transformation parameter generates

According to the method for the step 13 in said process (), input key file, generates the parameter a that becomes restoring transformation ₁, a ₂, a ₃and translation parameters e, f;

Step 22: the overall situation unrest that is inverted

A) according to going back raw parameter and inverse transformation rule, the inverse transformation of affined transformation is intended in pointwise; Meanwhile, need whether first judging point key element attribute z value be 0 when reduction; If 0, put key element sequence number y ' participation inverse operation; Otherwise z value replaces y ' participation inverse operation;

B) spatial data of will (x ', y ') locating a key element is all assigned to the some key element that (x, y) locates;

Step 23: after inverse transformation, carry out interlacing point key element by the sequence number of line face key element, a key element is added in corresponding line face key element one by one, form the line face figure layer data R after scramble ^dand show.

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